概括
本研究介绍了一种端到端物理层安全密钥生成和分发 (E2E-PLSKGD) 方法,使用光纤的错误向量阶段 (EVP). 它实现了高密钥生成率 (KGR) 和增强的安全性,而不需要额外的硬件.
科学领域:
- 光学通信是指光学通信.
- 网络安全 网络安全
- 人工智能的人工智能
背景情况:
- 现有的物理层安全密钥生成和分发 (PLSKGD) 方法面临兼容性,应用和密钥生成率 (KGR) 的限制.
- 强度调制信号通常由于振幅或相调制约束导致KGR不足.
研究的目的:
- 提出一个端到端的物理层安全密钥生成和分发 (E2E-PLSKGD) 方案,利用错误向量阶段 (EVP) 进行光纤传输.
- 通过使用人工智能驱动的建模,提高光纤系统的安全性和关键生成率.
主要方法:
- 引入了位置增强变压器 (PE-变压器) 架构,用于连贯光学系统的端到端 (E2E) 建模,具有自适应位置编码 (APC).
- 利用光纤系统中固有的相位随机性,为合法方构建E2E模型,计算错误向量,并将EVP噪声作为关键序列提取.
- 员工转移学习 (TL) 快速更新本地E2E源模型,以提高密钥安全性.
主要成果:
- 实现了优越的E2E建模,R-Square值>0.95和出色的波形拟合.
- 在合法政党之间证明了EVP序列的强烈相关性 (Pearson相关系数>0.8在50-80公里).
- 在120公里系统上实验验验证了0.72 EVP序列相关性,并在5G baud速率下实现0.8 Gbps的无错误KGR.
结论:
- 拟议的PE变压器架构允许精确的E2E建模,用于光纤系统中安全的密钥生成.
- 为动态,高质量的密钥生成提供了一种新的方法,增强光纤传输安全性.
- 突出了人工智能授权方法对未来安全光通信系统的潜力.
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